Ming Lin

1.7k citations
59 papers · 1.1k · h-index 16

Impact in

    • Human Pose and Action Recognition
    • Multimodal Machine Learning Applications
    • Video Analysis and Summarization
    • Video Surveillance and Tracking Methods
    • Advanced Neural Network Applications
    • Advanced Image and Video Retrieval Techniques
    • Anomaly Detection Techniques and Applications
    • Domain Adaptation and Few-Shot Learning

Papers in

Ming Lin

55 papers receiving 1.1k citations

Peers

Ming Lin
Comparison fields: 5 of 115
  • Computer Vision and Pattern Recognition 689
  • Artificial Intelligence 490
  • Signal Processing 104
  • Human-Computer Interaction 46
  • Media Technology 60
Replace Alessia Amelio with:
Alessia Amelio Italy
Sung-Jin Kim South Korea
Alex Hauptmann United States
Mostafa Dehghani Netherlands
Michihiko Minoh Japan
Hui-Huang Hsu Taiwan
Haim Levkowitz United States
Haidong Zhang China
Sanjay Kumar India
Ming Lin relative to Alessia Amelio Italy Alessia Amelio's profile →
Citations per field
00.5×2.7×
Alessia Amelio · 1×
Citations per year

Countries citing papers authored by Ming Lin

Since Specialization
Citations

This map shows the geographic impact of Ming Lin's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ming Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Lin more than expected).

Fields of papers citing papers by Ming Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ming Lin. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ming Lin. The network helps show where Ming Lin may publish in the future.

Co-authors

The 25 scholars most cited alongside Ming Lin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ming Lin Line = papers co-authored together Ming Lin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 59 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015200
2 2017165
3 202192
4 201575
5 202273
6 201661
7 200438
8 200638
9 200630
10 202029
11 200527
12 200821
13 201519
14
Online Kernel Learning with a Near Optimal Sparsity Bound
201317
15 201217
16 202416
17 201815
18 200314
19 200413
20 201410

About Ming Lin

Ming Lin is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Sociology and Political Science, Information Systems and Biomedical Engineering, having authored 59 papers that have together received 1.1k indexed citations. Recurring topics across this work include Video Analysis and Summarization (10 papers), Domain Adaptation and Few-Shot Learning (7 papers), Information and Cyber Security (7 papers), Human Pose and Action Recognition (5 papers), Face and Expression Recognition (5 papers), Sparse and Compressive Sensing Techniques (5 papers), Deception detection and forensic psychology (5 papers) and Machine Learning and Algorithms (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (689 citations), Artificial Intelligence (490 citations), Signal Processing (104 citations), Human-Computer Interaction (46 citations) and Media Technology (60 citations). Ming Lin has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Alexander G. Hauptmann, Yi Yang, Bhiksha Raj, Zhenzhong Lan, Xuanchong Li, Jay F. Nunamaker, Zhigang Ma, Xiaojun Chang, Alexander G. Hauptmann and Rong Jin. Their work appears in journals such as Journal of the Association for Information Systems, IEEE Transactions on Image Processing, IEEE Transactions on Neural Networks and Learning Systems, Applied Physics Letters and Applied Mathematics and Nonlinear Sciences.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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